Website University of Colorado Anschutz Medical Campus
Profile: Postdoctoral Fellow – Computational Biology / Machine Learning in Biology
Company: The Way Lab, University of Colorado Anschutz Medical Campus
Posted on: 11-04-22
Closing Date: 01-08-22
The Way Lab at the University of Colorado Denver Anschutz Medical Campus welcomes applications for computational biology postdoctoral positions.
The Way Lab’s mission is to integrate high-dimensional biomedical data into clinical decision-making and drug discovery. We are biologists who use data science to reduce human suffering. We develop and validate analytical methods, novel approaches, and write open-source software for the biology community. We aim to improve patient treatment strategies, discover biological mechanisms, and enable computational reproducibility with open source software.
We are currently focused on developing cell morphology as a systems biology measurement of cell state. We are establishing collaborations with academic and industry labs around the world to tackle challenging biomedical problems of today and tomorrow. Come join us to help shape our future and fulfill our mission!
Research projects center around developing machine learning methods to extract insights from high-dimensional systems biology assays. These assays may include transcriptomics, proteomics, cell morphology, and more. The candidate will be responsible for
(Postdoctoral Fellow – Computational Biology / Machine Learning)
- Developing methods and approaches to derive biologically-meaningful representations.
- Building new approaches to interpret these representations.
- Discovering mechanistic links between data types through methods for multi-modal data integration.
- Contributing to well-documented software.
- Participating and leading in team science collaborations with academic and industry lab.
Minimum Required Qualifications:
Applicants must meet minimum qualifications at the time of hire.
- Graduation from an accredited college or university with a PhD/MD in a relevant scientific discipline
- 3+ years of hands-on experience with common data science tools (e.g. Jupyter, github, pandas, dplyr, dask, sklearn, keras, pytorch, etc.)
The ideal candidate will have the following credentials:
- A strong background in biomedical data science, computer science, machine learning, statistics, genetics, cell biology, systems biology or a closely related field
- Programming experience (e.g. Python) with attributable contributions to source code
- Experience with computational reproducibility tools (e.g. Github, conda, snakemake)
- A track record of scientific productivity, leadership, and a commitment to your craft
Knowledge, Skills, and Abilities:
- Excellent oral and written communication skills
- Ability to learn and implement new technologies
- Experience handling large datasets in a UNIX/LINUX environment
- Experience with high-performance cluster or cloud computing
- Experience with data visualization tools (e.g. ggplot, seaborn, shiny) for effective data communication and publication
- Knowledge of existing software packages used for machine learning
- Ability to work independently and effectively with others as part of a multidisciplinary scientific team
Required Application Materials:
To apply, please visit: CU Careers (https://cu.taleo.net/careersection/2/jobdetail.ftl?job=25129&lang=en) and attach:
- A letter of application which specifically addresses the job requirements and outlines qualifications
- A current CV/resume
- List of three to five professional references (we will notify you prior to contacting both on and off-list references)
- A list of up to three links to publicly available source code repositories that you’ve contributed to
Visit CBIRT for more opportunities.
To apply for this job please visit cu.taleo.net.